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» Unsupervised Learning of Object Deformation Models
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CVPR
2010
IEEE
15 years 11 months ago
Latent Hierarchical Structural Learning for Object Detection
We present a latent hierarchical structural learning method for object detection. An object is represented by a mixture of hierarchical tree models where the nodes represent objec...
Leo Zhu, Yuanhao Chen, Antonio Torralba, Alan Yuil...
TSMC
2011
292views more  TSMC 2011»
15 years 6 days ago
Circular Blurred Shape Model for Multiclass Symbol Recognition
—In this paper, we propose a circular blurred shape model descriptor to deal with the problem of symbol detection and classification as a particular case of object recognition. ...
Sergio Escalera, Alicia Fornés, Oriol Pujol...
ICPR
2006
IEEE
16 years 6 months ago
Latent Layout Analysis for Discovering Objects in Images
Latent Layout Analysis (LLA) is a novel unsupervised learning technique to discover objects in unseen images using a set of un-annotated training images. LLA defines a generative ...
David Liu, Datong Chen, Tsuhan Chen
UAI
2004
15 years 6 months ago
Factored Latent Analysis for far-field Tracking Data
This paper uses Factored Latent Analysis (FLA) to learn a factorized, segmental representation for observations of tracked objects over time. Factored Latent Analysis is latent cl...
Chris Stauffer
ISVC
2010
Springer
15 years 3 months ago
Egocentric Visual Event Classification with Location-Based Priors
We present a method for visual classification of actions and events captured from an egocentric point of view. The method tackles the challenge of a moving camera by creating defor...
Sudeep Sundaram, Walterio W. Mayol-Cuevas